Automatic Approach for Word Sense Disambiguation Using Genetic Algorithms
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
Abstract
Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a collection of documents and produce's a lot of sense to the ambiguities word, the system creates dynamic, and up-todate word sense in a highly automatic method.
Authors and Affiliations
Dr. Bushra AlSaidi
Keywords
Related Articles
- EP ID EP106756
- DOI 10.14569/IJACSA.2016.070106
- Views 116
- Downloads 0
Design of Traffic Flow Simulation System to Minimize Intersection Waiting Time
This paper designs a traffic simulation system for minimizing intersection waiting time. We use SUMO simulator which is widely used as a traffic flow simulation tool for traffic flow simulation. Using the SUMO simulator...
A Real-Time Street Actions Detection
Human action detection in real time is one of the most important and challenging problems in computer vision. Nowadays, CCTV cameras exist everywhere in our lives. However, the contents of these cameras are monitored and...
Speaker Identification using Frequency Dsitribution in the Transform Domain
In this paper, we propose Speaker Identification using the frequency distribution of various transforms like DFT (Discrete Fourier Transform), DCT (Discrete Cosine Transform), DST (Discrete Sine Transform), Hartley...
Characterization of Dynamic Bayesian Network-The Dynamic Bayesian Network as temporal network
In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and L...
Intelligent Educational Assistant based on Multiagent System and Context-Aware Computing
This paper provides an overview of the current stage of EducActiveCore research, an orchestrated computational model, formed by different areas of artificial intelligent, combined to support personalized assistance to st...